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@j-min
j-min / korail_example.py
Last active Sep 15, 2019
Korean express train ticket reservation example
View korail_example.py
# pip install korail2
# https://github.com/carpedm20/korail2
from korail2 import Korail, NoResultsError, KorailError
from time import sleep
import os
# Login
EMAIL = '' # email
PW = '' # password
@j-min
j-min / test_single_gpu.py
Created Nov 6, 2016
TensorFlow single GPU example
View test_single_gpu.py
from __future__ import print_function
'''
Basic Multi GPU computation example using TensorFlow library.
Author: Aymeric Damien
Project: https://github.com/aymericdamien/TensorFlow-Examples/
'''
'''
This tutorial requires your machine to have 1 GPU
"/cpu:0": The CPU of your machine.
@j-min
j-min / download_video.py
Created Jul 1, 2019
Youtube Video Download & Trim
View download_video.py
# https://github.com/mps-youtube/pafy
import pafy
if __name__ == '__main__':
video_url = 'https://www.youtube.com/watch?v=D_Ij3fAps4s'
video = pafy.new(video_url)
print(video.title, video.duration)
best = video.getbest()
best.download(quiet=False)
@j-min
j-min / .vimrc
Last active Apr 28, 2019
vimrc plugin settings for Python / JavaScript
View .vimrc
set nocompatible " required
" filetype off " required
syntax on
syntax enable
" Monokai color scheme
" mkdir -p ~/.vim/colors
" wget https://raw.githubusercontent.com/crusoexia/vim-monokai/master/colors/monokai.vim ~/.vim/colors
colorscheme monokai
@j-min
j-min / RNN_hunkim's_tutorial_BasicRNNCell.ipynb
Last active Dec 11, 2018
TensorFlow 0.9 implementation of BasicRNNCell based on hunkim's tutorial
View RNN_hunkim's_tutorial_BasicRNNCell.ipynb
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@j-min
j-min / test_multi_gpu.py
Last active Nov 28, 2018
TensorFlow multi GPU example
View test_multi_gpu.py
from __future__ import print_function
'''
Basic Multi GPU computation example using TensorFlow library.
Author: Aymeric Damien
Project: https://github.com/aymericdamien/TensorFlow-Examples/
'''
'''
This tutorial requires your machine to have 2 GPUs
"/cpu:0": The CPU of your machine.
@j-min
j-min / backprop.ipynb
Created Mar 1, 2017
Simple backprop implementation in TensorFlow without its optimizer API
View backprop.ipynb
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@j-min
j-min / exp_lr_scheduler.py
Created Jun 25, 2017
learning rate decay in pytorch
View exp_lr_scheduler.py
# http://pytorch.org/tutorials/beginner/transfer_learning_tutorial.html
def exp_lr_scheduler(optimizer, epoch, init_lr=0.001, lr_decay_epoch=7):
"""Decay learning rate by a factor of 0.1 every lr_decay_epoch epochs."""
lr = init_lr * (0.1**(epoch // lr_decay_epoch))
if epoch % lr_decay_epoch == 0:
print('LR is set to {}'.format(lr))
for param_group in optimizer.param_groups:
View tensorboard_inline.py
from IPython.display import clear_output, Image, display, HTML
import numpy as np
def strip_consts(graph_def, max_const_size=32):
"""Strip large constant values from graph_def."""
strip_def = tf.GraphDef()
for n0 in graph_def.node:
n = strip_def.node.add()
n.MergeFrom(n0)
if n.op == 'Const':
@j-min
j-min / tmux_install.sh
Last active Nov 10, 2017
tmux 2.6 install script (linux)
View tmux_install.sh
TMUX_VERSION=2.6
cd $HOME
# Dependencies
sudo apt install libevent-dev ncurses-dev -y
# Download tmux
wget https://github.com/tmux/tmux/releases/download/$TMUX_VERSION/tmux-$TMUX_VERSION.tar.gz
tar -xvzf tmux-$TMUX_VERSION.tar.gz
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